We are interested in learning why patients are experiencing long wait times and how this is impacting both their experience and the standard of care we provide. The objective is to:

Determine the reason behind the delays in making appointments and visiting the clinic.

To find out how wait times are affecting patients and staff, get their opinions.

Determine doable and realistic measures to reduce wait times.

Enhance overall patient satisfaction and improve the effectiveness of our service.

2. Data collection methods: What methods will you use to collect data?

Quantitative (based on numbers) approaches:

Audits of appointments. We will examine wait times, the frequency of appointment misses, and the ratio of available to booked appointments (DNAs).

Surveys of patients: We will directly ask patients about their opinions of the current system, particularly regarding waiting times and booking procedures.

Qualitative (based on feedback) techniques:

Staff discussions: To determine what is and is not working, conduct focus groups or informal interviews with GPs, nurses, and reception staff to gather feedback.

Patient stories: Compiling feedback from patients (through online reviews, suggestion boxes, or interviews) in order to understand the human aspect of the problem.

3. Data analysis techniques: How will you analyse the data (e.g., quantitative analysis, qualitative analysis)?

We will employ a variety of strategies:

For the numbers, we will figure out averages (such as the number of days people wait for appointments), identify patterns, and look for trends (such as the most common times for delays).

Regarding the feedback, we will review the remarks made by patients and staff to identify recurring themes, such as annoyance with reservation systems or communication issues.

4. Key performance indicators (KPIs): What metrics will you use to measure performance?

The following metrics will be used to monitor improvements:

Reduced average wait times for routine GP appointments, ideally less than five working days.

There are more same-day appointments available.

Higher patient satisfaction ratings, particularly about waiting and access.

Reduced appointment-missing rates (DNAs).

Fewer complaints of overworked or overburdened employees.

5. Timeline

Timeline for Steps

Organising and involving the group. Week 1: Data collection (audits, surveys), Interviews with staff and patients in weeks two and four. Weeks three and four

Examining what we have discovered: 5. Developing our plan for improvement, 6. Presenting results and subsequent actions. Week 7: Modifications and idea testing. Weeks 8–10

Examining the progress from Weeks 12–14

Enhancement

Here are some initial ideas, but we will customise solutions once we have the data:

Triage appointments enable routine cases to be handled more efficiently and urgent cases to be seen more promptly.

Consultations over the phone or online: To relieve the strain on in-person appointments.

Staffing reviews: determining whether additional GP or nurse sessions are required during busy periods.

Improved communication: Informing patients of anticipated wait times and the causes of delays.

Look at the factors affecting long waiting times ie staff shortages, high need and patient backlog of services.

Data collection methods: What methods will you use to collect data ? – patient feedback (written and digital), service performance data

Data analysis techniques: How will you analyse the data – Qualitative /quantitate analysis 

Key performance indicators (KPIs): What metrics will you use to measure performance? Task completion rate, staff performance, staffing number data, rate of staff absence, lack of funding, good patient experiences.

Timeline: When will you collect and analyse the data? – up to 1 year 

Reduce patient waiting times for appointments

·        Data collection methods: 

Survey from staff

Survey from patients

Number of missed appointments audit

Average total appointment time audit

Primary concern for appointments audit

Staff capacity and skill set audit

• Data analysis techniques: 

Quantitative analysis of missed appointments, average appointment duration and reasons for appointments

Qualitative analysis of staff concerns and patient concerns

• Key performance indicators (KPIs): 

More appointment attendance/adherence by patients

Better quality of appointments to reduce reoccurrence

• Timeline: When will you collect and analyse the data?

Initial study timeline – collected over 3-6 months

Implementation – 3-6 months

Patient and staff feedback to be collected over the course of implementation phase and applied to continuous improvement framework.

-Staffing issues?

-Internal changes to the surgery

- Text survey

- In person

-Try to ask each person each appt.

- Email

- GPAD

analysis:

-Quant. demographics of area/changes

-Quant. volume of conditions frequently encountered

-Quant. staffing changes

-Quant. appointment time/changes

-Qual. health conditions creating need for appointments

-Qual. patient experiences

-Qual. whether patients are having all needs met during appointments/being told to make extra for each concern.

-Satisfaction scales

-Self-described health rating

-First response time

-Resolution time/rate

-Error rate

-Spot check patients since the waiting times have increased

-Monthly reviews minimum

1. Identify primary causes of appointment delays and patient dissatisfaction.

2. Assess operational efficiency and demand-capacity balance.

3. Measure the effectiveness of booking and triage systems.

4. Develop an evidence-based improvement plan to reduce average wait time and enhance patient experience.

Data Collection Methods

Technique

Reason

Patient surveys

Gain perceptions of accessibility, delays, and satisfaction

Staff interviews/focus groups

Figure out workflow pressures, triage delays, and scheduling issues

System audit

Study appointment slot data, DNAs, and clinician utilisation

Review of complaint logs

Identify themes and root causes related to long waits

Real-time observation

Observe bottlenecks in reception and triage in peak periods

Data Analysis Techniques

Quantitative analysis:

-            Descriptive statistics (mean, median wait times, DNA rates)

-            Time series analysis (e.g., appointment delays over the past 3–6 months)

-            Compare against national benchmarks (e.g., NHSE GP appointment data)

• Qualitative analysis:

• Thematic coding of patient/staff feedback

• Root cause analysis of complaint cases

• Reflective content analysis on service pathways

Key Performance Indicators (KPIs)

Indicator

Target

Average wait time for routine appointments

DNA rate

<5%

Percentage of patients satisfied with access

>85% (Friends & Family Test)

% of calls answered within 2 minutes

≥90% during working hours

Patient complaints related to wait time

Reduction by ≥25% in 3 months

Project Timeline

Stage

Timeframe

Scoping & stakeholder briefing

Week 1

Data collection

Weeks 2–4

Data analysis

Weeks 5–6

Feedback & recommendations

Week 7

Implementation of pilot change

Week 8 onwards

Post-implementation review

Weeks 12–14